| Records |
| Author |
Sanchis-Lozano, M.A.; Sarkisyan-Grinbaum, E. |
Title  |
A correlated-cluster model and the ridge phenomenon in hadron-hadron collisions |
Type |
Journal Article |
| Year |
2017 |
Publication |
Physics Letters B |
Abbreviated Journal |
Phys. Lett. B |
| Volume |
766 |
Issue |
|
Pages |
170-176 |
| Keywords |
pp interactions at LHC; Heavy-ion collisions at RHIC and LHC; Ridge phenomenon; Correlated clusters; Two-particle azimuthal and rapidity correlations |
| Abstract |
A study of the near-side ridge phenomenon in hadron-hadron collisions based on a cluster picture of multiparticle production is presented. The near-side ridge effect is shown to have a natural explanation in this context provided that clusters are produced in a correlated manner in the collision transverse plane. |
| Address |
[Sanchis-Lozano, Miguel-Angel] Ctr Mixto Univ Valencia, CSIC, Inst Fis Corpuscular IFIC, Dr Moliner 50, E-46100 Burjassot, Spain, Email: Miguel.Angel.Sanchis@ific.uv.es; |
| Corporate Author |
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Thesis |
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| Publisher |
Elsevier Science Bv |
Place of Publication |
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Editor |
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| Language |
English |
Summary Language |
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Original Title |
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| Series Editor |
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Series Title |
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Abbreviated Series Title |
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| Series Volume |
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Series Issue |
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Edition |
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| ISSN |
0370-2693 |
ISBN |
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Medium |
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| Area |
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Expedition |
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Conference |
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| Notes |
WOS:000396438300025 |
Approved |
no |
| Is ISI |
yes |
International Collaboration |
yes |
| Call Number |
IFIC @ pastor @ |
Serial |
3002 |
| Permanent link to this record |
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| Author |
Hirn, J.; Garcia, J.E.; Montesinos-Navarro, A.; Sanchez-Martin, R.; Sanz, V.; Verdu, M. |
| Title |
A deep Generative Artificial Intelligence system to predict species coexistence patterns |
Type |
Journal Article |
| Year |
2022 |
Publication |
Methods in Ecology and Evolution |
Abbreviated Journal |
Methods Ecol. Evol. |
| Volume |
13 |
Issue |
|
Pages |
1052-1061 |
| Keywords |
artificial intelligence; direct interactions; generative adversarial networks; indirect interactions; species coexistence; variational AutoEncoders |
| Abstract |
Predicting coexistence patterns is a current challenge to understand diversity maintenance, especially in rich communities where these patterns' complexity is magnified through indirect interactions that prevent their approximation with classical experimental approaches. We explore cutting-edge Machine Learning techniques called Generative Artificial Intelligence (GenAI) to predict species coexistence patterns in vegetation patches, training generative adversarial networks (GAN) and variational AutoEncoders (VAE) that are then used to unravel some of the mechanisms behind community assemblage. The GAN accurately reproduces real patches' species composition and plant species' affinity to different soil types, and the VAE also reaches a high level of accuracy, above 99%. Using the artificially generated patches, we found that high-order interactions tend to suppress the positive effects of low-order interactions. Finally, by reconstructing successional trajectories, we could identify the pioneer species with larger potential to generate a high diversity of distinct patches in terms of species composition. Understanding the complexity of species coexistence patterns in diverse ecological communities requires new approaches beyond heuristic rules. Generative Artificial Intelligence can be a powerful tool to this end as it allows to overcome the inherent dimensionality of this challenge. |
| Address |
[Hirn, Johannes; Enrique Garcia, Jose; Sanz, Veronica] Univ Valencia, CSIC, Inst Fis Corpuscular IFIC, Valencia, Spain, Email: miguel.verdu@ext.uv.es |
| Corporate Author |
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Thesis |
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| Publisher |
Wiley |
Place of Publication |
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Editor |
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| Language |
English |
Summary Language |
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Original Title |
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| Series Editor |
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Series Title |
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Abbreviated Series Title |
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| Series Volume |
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Series Issue |
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Edition |
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| ISSN |
2041-210x |
ISBN |
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Medium |
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| Area |
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Expedition |
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Conference |
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| Notes |
WOS:000765239700001 |
Approved |
no |
| Is ISI |
yes |
International Collaboration |
yes |
| Call Number |
IFIC @ pastor @ |
Serial |
5155 |
| Permanent link to this record |
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| Author |
Gonzalez-Sevilla, S. et al; Bernabeu Verdu, J.; Civera, J.V.; Garcia, C.; Lacasta, C.; Marco, R.; Marti-Garcia, S.; Santoyo, D.; Soldevila, U. |
| Title |
A double-sided silicon micro-strip Super-Module for the ATLAS Inner Detector upgrade in the High-Luminosity LHC |
Type |
Journal Article |
| Year |
2014 |
Publication |
Journal of Instrumentation |
Abbreviated Journal |
J. Instrum. |
| Volume |
9 |
Issue |
|
Pages |
P02003 - 37pp |
| Keywords |
Particle tracking detectors; Si microstrip and pad detectors; Performance of High Energy Physics Detectors |
| Abstract |
The ATLAS experiment is a general purpose detector aiming to fully exploit the discovery potential of the Large Hadron Collider (LHC) at CERN. It is foreseen that after several years of successful data-taking, the LHC physics programme will be extended in the so-called High-Luminosity LHC, where the instantaneous luminosity will be increased up to 5 x 10(34) cm(-2) s(-1). For ATLAS, an upgrade scenario will imply the complete replacement of its internal tracker, as the existing detector will not provide the required performance due to the cumulated radiation damage and the increase in the detector occupancy. The current baseline layout for the new ATLAS tracker is an all-silicon-based detector, with pixel sensors in the inner layers and silicon micro-strip detectors at intermediate and outer radii. The super-module is an integration concept proposed for the strip region of the future ATLAS tracker, where double-sided stereo silicon micro-strip modules are assembled into a low-mass local support structure. An electrical super-module prototype for eight double-sided strip modules has been constructed. The aim is to exercise the multi-module readout chain and to investigate the noise performance of such a system. In this paper, the main components of the current super-module prototype are described and its electrical performance is presented in detail. |
| Address |
[Gonzalez-Sevilla, S.; Barbier, G.; Cadoux, F.; Clark, A.; Favre, Y.; Ferrere, D.; Iacobucci, G.; La Marra, D.; Weber, M.] DPNC Univ Geneva, Geneva, Switzerland, Email: rgio.Gonzalez.Sevilla@cern.ch |
| Corporate Author |
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Thesis |
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| Publisher |
Iop Publishing Ltd |
Place of Publication |
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Editor |
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| Language |
English |
Summary Language |
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Original Title |
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| Series Editor |
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Series Title |
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Abbreviated Series Title |
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| Series Volume |
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Series Issue |
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Edition |
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| ISSN |
1748-0221 |
ISBN |
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Medium |
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| Area |
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Expedition |
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Conference |
|
| Notes |
WOS:000332314400038 |
Approved |
no |
| Is ISI |
yes |
International Collaboration |
yes |
| Call Number |
IFIC @ pastor @ |
Serial |
1749 |
| Permanent link to this record |
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| Author |
Diez, S. et al; Bernabeu Verdu, J.; Civera, J.V.; Garcia, C.; Garcia-Argos, C.; Lacasta, C.; Marco, R.; Marti-Garcia, S.; Santoyo, D.; Soldevila, U. |
| Title |
A double-sided, shield-less stave prototype for the ATLAS Upgrade strip tracker for the High Luminosity LHC |
Type |
Journal Article |
| Year |
2014 |
Publication |
Journal of Instrumentation |
Abbreviated Journal |
J. Instrum. |
| Volume |
9 |
Issue |
|
Pages |
P03012 - 16pp |
| Keywords |
Large detector-systems performance; Si microstrip and pad detectors; Particle tracking detectors; Performance of High Energy Physics Detectors |
| Abstract |
A detailed description of the integration structures for the barrel region of the silicon strips tracker of the ATLAS Phase-II upgrade for the upgrade of the Large Hadron Collider, the so-called High Luminosity LHC (HL-LHC), is presented. This paper focuses on one of the latest demonstrator prototypes recently assembled, with numerous unique features. It consists of a shortened, shield-less, and double sided stave, with two candidate power distributions implemented. Thermal and electrical performances of the prototype are presented, as well as a description of the assembly procedures and tools. |
| Address |
[Diez, S.; Haber, C. H.; Witharm, R.] LBNL, Berkeley, CA 94103 USA, Email: sdiezcornell@lbl.gov |
| Corporate Author |
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Thesis |
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| Publisher |
Iop Publishing Ltd |
Place of Publication |
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Editor |
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| Language |
English |
Summary Language |
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Original Title |
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| Series Editor |
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Series Title |
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Abbreviated Series Title |
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| Series Volume |
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Series Issue |
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Edition |
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| ISSN |
1748-0221 |
ISBN |
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Medium |
|
| Area |
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Expedition |
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Conference |
|
| Notes |
WOS:000336123200072 |
Approved |
no |
| Is ISI |
yes |
International Collaboration |
yes |
| Call Number |
IFIC @ pastor @ |
Serial |
1802 |
| Permanent link to this record |
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| Author |
Panotopoulos, G. |
| Title |
A dynamical dark energy model with a given luminosity distance |
Type |
Journal Article |
| Year |
2011 |
Publication |
General Relativity and Gravitation |
Abbreviated Journal |
Gen. Relativ. Gravit. |
| Volume |
43 |
Issue |
11 |
Pages |
3191-3199 |
| Keywords |
Dark energy; Observational cosmology; Particle-theory |
| Abstract |
It is assumed that the current cosmic acceleration is driven by a scalar field, the Lagrangian of which is a function of the kinetic term only, and that the luminosity distance is a given function of the red-shift. Upon comparison with baryon acoustic oscillations and cosmic microwave background data the parameters of the models are determined, and then the time evolution of the scalar field is determined by the dynamics using the cosmological equations. We find that the solution is very different than the corresponding solution when the non-relativistic matter is ignored, and that the universe enters the acceleration era at larger red-shift compared to the standard I > CDM model. |
| Address |
[Panotopoulos, G] Univ Valencia, Dept Fis Teor, E-46100 Burjassot, Spain, Email: Grigoris.Panotopoulos@uv.es |
| Corporate Author |
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Thesis |
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| Publisher |
Springer/Plenum Publishers |
Place of Publication |
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Editor |
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| Language |
English |
Summary Language |
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Original Title |
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| Series Editor |
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Series Title |
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Abbreviated Series Title |
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| Series Volume |
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Series Issue |
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Edition |
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| ISSN |
0001-7701 |
ISBN |
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Medium |
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| Area |
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Expedition |
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Conference |
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| Notes |
WOS:000295982800015 |
Approved |
no |
| Is ISI |
yes |
International Collaboration |
no |
| Call Number |
IFIC @ elepoucu @ |
Serial |
782 |
| Permanent link to this record |
